[nltk_data] Downloading package stopwords to /root/nltk_data... [nltk_data] Unzipping corpora/stopwords.zip.
This document processes the outputs of the praise reward system and performs an analysis of the resulting token reward distribution.
Since praise gets valued on a scale, we can take a look at how often each value of the scale gets assigned by quantifiers. Note: This metric disregards scores of praise marked as a duplicate, since the score of the original is already being taken into account.
The ten highest rated contributions for this round were the following:
| Avg. score | To | Reason |
|---|---|---|
| 55.0 | ALOYSIOUS#3049 | for willingness to share knowledge and support us in curating Identity exploration content that will explore the inclusive culture in the Public Goods space |
| 41.0 | Yineisy Mota#1449 | @Yineisy Mota for their ideas, availability and contributions to acknowledging Identity Spectrum. |
| 32.33 | mafer_cordovas#1034 | @Yineisy Mota for their ideas, availability and contributions to acknowledging Identity Spectrum. |
| 31.0 | Yineisy Mota#1449 | @Yineisy Mota for mentioning or retweeting Commons Stack on the socials the past week! Thank you for helping us grow the Commons Stack community and spreading the message! 🙏🏼🌱 |
| 31.0 | logonaut.eth#9437 | for mentioning or retweeting Commons Stack on the socials the past week! Thank you for helping us grow the Commons Stack community and spreading the message! 🙏🏼🌱 |
| 19.0 | mafer_cordovas#1034 | @Yineisy Mota for mentioning or retweeting Commons Stack on the socials the past week! Thank you for helping us grow the Commons Stack community and spreading the message! 🙏🏼🌱 |
| 10.23 | logonaut.eth#9437 | @Yineisy Mota for mentioning or retweeting Commons Stack on the socials the past week! Thank you for helping us grow the Commons Stack community and spreading the message! 🙏🏼🌱 |
| 7.67 | mafer_cordovas#1034 | for their super supportive attitude, and their alertness in Twitter to possibilities for CS and TEC, I hope to build on that immediately. |
| 6.33 | freshelle#9882 | for being so supportive of me today and helping me with my trace 🙏 🥺 |
| 2.33 | mafer_cordovas#1034 | for mentioning or retweeting Commons Stack on the socials the past week! Thank you for helping us grow the Commons Stack community and spreading the message! 🙏🏼🌱 |
We can now take a look at the distribution of the received praise rewards. You can toggle the inclusion of the different sources by clicking on the legend.
We can also take a look at the amount of praise different users gave.
Now for something more fun: let's surface the top "praise flows" from the data. Thanks to @inventandchill for this awesome visualization! On one side we have the top 15 praise givers separately, on the other the top 25 receivers. The people outside the selection get aggregated into the "REST FROM" and "REST TO" categories.
Now let's take a closer look at the quantification process and the quantifiers:
To aid the revision process, we highlight disagreements between quantifiers.
This graphic visualizes controversial praise ratings by sorting them by the "spread" between the highest and lowest received score.
Please keep in mind that this is a visual aid. If there are several praise instances with similar spread and quant score, all but one end up "hidden" on the chart. For an exhaustive list, take a look at the exported file "praise_outliers.csv" .
Let's see how different quantifiers behaved by showing the range of praise scores they gave.
To interpret the box plot:
Bottom horizontal line of box plot is minimum value
First horizontal line of rectangle shape of box plot is First quartile or 25%
Second horizontal line of rectangle shape of box plot is Second quartile or 50% or median.
Third horizontal line of rectangle shape of box plot is third quartile or 75%
Top horizontal line of rectangle shape of box plot is maximum value.
Among 22 praises, 1 (4.55%) do not agree on duplication
Praise instances with disagreements in duplication are collected in 'results/duplication_examination.csv'. To compare, look at the last 4 columns: 'DUPLICATE MSG 1/2/3' and 'ORIGINAL MSG'.
Among 22 praises, 0 (0.00%) do not agree on dismissal
Praise instances with disagreements in dismissal are collected in'results/dismissal_disaggreed.csv'. You can further look into who dismissed and who did not.